Yuki Kadokawa

Current Position

Institute: Nara Institute of Science and Technology

Position: Project Assistant Professor

Education

• Doctor of Engineering, Nara Institute of Science and Technology, Program of Information Science and Engineering, Japan, 2024
• Master of Engineering, Nara Institute of Science and Technology, Program of Information Science and Engineering, Japan, 2021
• Bachelor of Engineering, Toyama Prefectural University, Department of Intelligent Robotics, Japan, 2019

Publicatin

International Journal

1. Yuki Kadokawa, Hirotaka Tahara, and Takamitsu Matsubara, "Progressive-Resolution Policy Distillation: Leveraging Coarse-Resolution Simulations for Time-Efficient Fine-Resolution Policy Learning", under review
2. Yuki Kadokawa, Tomohito Kodera, Yoshihisa Tsurumine, Shinya Nishimura, and Takamitsu Matsubara, "Robust Iterative Value Conversion: Deep Reinforcement Learning for Neurochip-driven Edge Robots", Robotics and Autonomous Systems (RAS), 2024 [Paper] [Video]
3. Yuki Kadokawa, Lingwei Zhu, Yoshihisa Tsurumine and Takamitsu Matsubara, "Cyclic Policy Distillation: Sample-Efficient Sim-to-Real Reinforcement Learning with Domain Randomization", Robotics and Autonomous Systems (RAS), 2023 [Paper] [Video]
4. Yuki Kadokawa, Yoshihisa Tsurumine, and Takamitsu Matsubara, "Binarized P-Network: Deep Reinforcement Learning of Robot Control from Raw Images on FPGA", IEEE Robotics and Automation Letters (RA-L), vol. 6, no. 4, pp. 8545-8552, 2021 (Student Paper Award) [Paper] [Video]

International Conference

1. Ryo Watanabe, Takahiro Miki, Fan Shi, Yuki Kadokawa, Filip Bjelonic, Kento Kawaharazuka, Andrei Cramariuc, and Marco Hutter, "Learning Quiet Walking for a Small Home Robot", International Conference on Robotics and Automation (ICRA), 2025 [Project Page] [Paper] [Video]
2. Yuki Kadokawa, and Takamitsu Matsubara, "Scalable Domain Randomized Reinforcement Learning for Sim-to-Real Policy Transfer in Complex Robot Tasks", International Symposium on Artificial Life and Robotics (AROB), 2025 [Conference URL]
3. Yuki Kadokawa, Masashi Hamaya, and Kazutoshi Tanaka, "Learning Robotic Powder Weighing from Simulation for Laboratory Automation", IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023 [Project Page] [Paper] [Video]
4. Yuki Kadokawa, Yoshihisa Tsurumine, and Takamitsu Matsubara, "Binarized P-Network: Deep Reinforcement Learning of Robot Control from Raw Images on FPGA", IEEE International Conference on Robotics and Automation (ICRA, RA-L option), 2023 [Paper] [Video]

Domestic Conference

1. Alonso Ramos Fernandez, Yuki Kadokawa, Yoshihisa Tsurumine, and Takamitsu Matsubara, "Deep Reinforcement Learning with FPNN-toSNN Policy Distillation for Neurochip-driven Robots", Annual Conference of the Robotics Society of Japan, 2024 (Best Presentation Award Finalist) [Conference URL]
2. 中村維冴, 山之口智也, 角川勇貴, 曲佳, 大坪舜, 三輪祥太郎, 松原崇充, "Sim-to-Real 方策転移のためのダイナミクスランダム化対照強化学習", ロボティクス・メカトロニクス講演会, 2024 [Conference URL]
3. 小寺智仁, 角川勇貴, 鶴峯義久, 松原崇充, "ニューロチップ実装に適した量子化方策のエッジサーバー深層強化学習", 計測自動制御学会制御部門マルチシンポジウム, 2023 [Conference URL]
4. 角川勇貴, 鶴峯義久, 松原崇充, "FPGAを用いた実時間ロボット制御のための深層強化学習手法 Binary P-Network の提案", 日本ロボット学会学術講演会, 2020 [Conference URL]

Award

1. Nara Institute of Science and Technology, Symposium of University Fellowship, Outstanding Student Award, 2022 [Award Page]
2. IEEE Kansai Section, Student Paper Award, 2022 Student Award, 2022 [NAIST Award Page] [IEEE Award Page]
3. Toyama Prefectural University, Best Student of the Year, 2019
4. Toyama Mechanical and Electrical Industries Association, Monozukuri in Toyama, Grand Prize, 2018
5. Japan Society for Design Engineering, Design Competition, Best Presentation Award, 2018
6. Japan Society for Design Engineering, Design Competition, 3rd Place (National Finals 3/10), 2018
7. Japan Society for Design Engineering, Research Presentation, Best Student Presentation Award, 2018
8. Japan Society for Design Engineering, Design Competition, Best Presentation Award, 2017
9. Toyama Prefectural Takaoka Kogei High School, Best Student of the Year, 2015

Scholarship & Grant

1. Nara Institute of Science and Technology, Senju Monju Project (Obtaining Research Grant), 2024-2026
2. Japan Student Services Organization, Scholarship (Return Exemption Full Amount), 2023
3. Japan Society for the Promotion of Science, Research Fellowship for Young Scientists: DC2 (Obtaining Research Funding and Salaries), 2023-2025
4. Japan Science and Technology Agency, Research Fellowship (Obtaining Research Grant and Salaries), 2022-2023 [Interview Page]
5. Japan Student Services Organization, Scholarship (Return Exemption Half Amount), 2021
6. Nara Institute of Science and Technology, Outstanding Student Scholarship (Tuition Exemption), 2021

Work history

1. August 2023 - October 2023, Robotics Systems Lab (ETH Zurich), Visiting Researcher
2. April 2022 - March 2023, OMRON SINIC X Corporation, Research Internship [Project Page] [Paper] [Video]
3. December 2018 - March 2019, Aluminum Factory Corporation, Part-time Job for Making 3D-CAD Models

Research Field

• Reinforcement Learning, Deep Learning, Robotics
• Sim-to-Real, Domain Randomization
• Edge Robot, FPGA, Neurochip